<p>Bike-sharing programs, with the flexibility of on-demand pick-up and drop-off, are a valuable complement to public transport, particularly in addressing the “last mile” problem. Understanding bike-sharing patterns around metro stations is crucial for optimizing urban mobility. This study develops a framework that combines descriptive and quantitative methods to analyze the spatio-temporal distribution and determinants of bike-sharing usage in metro station areas using trip data. The findings reveal three distinct usage patterns in these areas. Furthermore, from the perspective of scaling laws, spatio-temporal heterogeneity in usage distribution has been thoroughly confirmed, with bike-sharing trips exhibiting a differentiated power–law distribution on typical days and a truncated power–law distribution during peak hours. Additionally, factors such as metro station network design, the built environment, and socio-demographic characteristics significantly influence bike-sharing usage. These results offer valuable insights into integrating bike-sharing with metro systems, providing a theoretical foundation for the planning of bike-sharing stations near metro hubs and supporting TOD strategies.</p>